Triple

T981640
Position Surface form Disambiguated ID Type / Status
Subject Walden Two E21180 entity
Predicate featuresCharacter P626 FINISHED
Object Rogers E773 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rogers | Statement: [Walden Two, featuresCharacter, Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rogers
Context triple: [Walden Two, featuresCharacter, Rogers]
  • A. Rogers chosen
    Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • B. Rogers
    Rogers is a growing city in northwestern Arkansas known for its role in the Fayetteville–Springdale–Rogers metropolitan area and as a regional commercial and retail hub.
  • C. Rogers & Wells
    Rogers & Wells was a prominent New York-based law firm known for its corporate and international legal practice before merging into Clifford Chance in 2000.
  • D. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • E. Otis
    Otis is a globally recognized manufacturer of elevators, escalators, and moving walkways, known for pioneering vertical transportation technologies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b47cbca48190a01880bb411e80bd completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1ce14ffc8190b2d0a7915960ff89 completed March 7, 2026, 12:41 p.m.
Created at: March 1, 2026, 7:41 p.m.